The language of telemedicine: In your patient’s words

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While telemedicine providers and service representatives might be familiar with medical terminology, you can bet most patients aren’t.

As technology becomes more embedded into the healthcare experience, providers need to find new ways to bridge the gap in understanding. One way to do this is with technology that translates patient language into clinical terminology. This can deliver a more satisfying patient experience and reduce errors. The same technology can also be used to convert patient input into medical codes. And that supports a more efficient billing and reimbursement workflow for telemedicine providers.

Natural language processing (NLP) is a technology that allows computers and other devices to capture and process information—whether spoken or typed—from humans. For the first time ever, telemedicine companies are using NLP to convert consumer or patient free-text into medical terminology and codes.

NLP facilitates the first step of a medical encounter and eliminates the need for telemedicine providers and staff to look up clinical codes. Why does this matter? In any medical encounter, including telemedicine visits, a clinician or other service provider collects information and gives it to a medical billing and coding specialist. That specialist then translates the information about the interaction and the service provided into medical codes. This can be a complex and timely process. Having a standardized set of clinically coded complaints simplifies this process and can save money for the provider and the patient.

Unexpected benefits of NLP
A single bump in the road while coding can cause a ripple effect, which can delay billing and reimbursement. Evolving uses of NLP and medical coding can alleviate the pressure on clinicians and coding specialists by allowing them to collect useful information.

For example, Health Navigator experts analyzed data from nearly 20,000 interactions at medical call centers across the country. Their goal was to gather data using NLP to identify the most common complaints in different age groups, how urgent their symptoms were and the time they called. The coded information allowed the team to identify chief complaints, analyze symptom urgency and track the call information in medical terms. Data about how often patients call for certain complaints or needs can help telemedicine providers better plan workflow and train staff. It can also influence patient education and follow-up activities.

Having NLP as the first step in an mHealth or telemedicine encounter paves the way for other steps of a traditional medical encounter. This process enables telemedicine providers to accurately and efficiently capture patient symptoms in the first step. But it also facilitates the middle of a medical encounter with follow-up questions and documentation support. The pre-visit documentation produced can speed up the diagnostic process and reduce unnecessary visits.

NLP also provides benefits for patients, which influences customer satisfaction and overall retention. Being able to analyze and interpret what a patient says or the information they type (including common misspellings and grammatical errors), supports health literacy principles with easy-to-understand tools at an average reading level. It also allows patients to experience the familiar first step of a medical encounter.

Improving health literacy matters because patients who don’t understand or act on their health needs are more likely to need complex care down the road. NLP can help healthcare providers overcome the barrier of limited literacy and deliver a consistent, standardized experience for all patients.

The bonus: patients who understand healthcare often take a more active role in managing their health, which leads to better engagement and satisfaction. And happy patients are more likely to become repeat users of a telemedicine platform they trust.

An engagement solution
NLP is an engagement solution for patients, and a communication and documentation solution for telemedicine providers. This first step of the medical encounter provides patients with a familiar process in a digital format. It also simplifies the medical coding and billing process, and improves efficiencies by providing data that can be shared among medical call center nurses, telemedicine providers, hospitals and primary care providers.

As technology in healthcare continues to advance, solutions like NLP will also evolve to address the changing needs of healthcare and telemedicine providers. By integrating patient- and clinician-friendly technology into the traditional medical encounter, providers can stay competitive in the growing digital healthcare landscape.

About the author
Amy Window serves as vice president of business development for Health Navigator, Inc. Amy brings 17 years of experience in healthcare software and client relations to Health Navigator, where she is charged with engaging with new partners and ensuring client success. Prior to Health Navigator, Amy worked in roles ranging from director of product development, and national sales director for companies within the telemedicine space such as Medweb, ViTelNet, and Air Methods.

The views, opinions and positions expressed within these guest posts are those of the author alone and do not represent those of Becker's Hospital Review/Becker's Healthcare. The accuracy, completeness and validity of any statements made within this article are not guaranteed. We accept no liability for any errors, omissions or representations. The copyright of this content belongs to the author and any liability with regards to infringement of intellectual property rights remains with them.

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